Encryption of Multimodal Features Enhances Security for Physical Characters of Biometrics: A Bio-Crypto System

Encryption of Multimodal Features Enhances Security for Physical Characters of Biometrics: A Bio-Crypto System

Nisha.S, Prasthuthi Raj, Shreya B, Sanika MS, Bhoomika BK

CSE, Presidency University, Bangalore, Karnataka, India

CSE, Presidency University, Bangalore, Karnataka, India

CSE, Presidency University, Bangalore, Karnataka, India

CSE, Presidency University, Bangalore, Karnataka, India

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Abstract—AI-Powered Malware Detection for Modern Cyber Threats

The increasing reliance on biometric authentication systems necessitates enhanced security to protect sensitive data. This study introduces a bio-crypto system that combines iris and face biometrics to generate a biometric key for authentication and confidentiality. By employing feature extraction through machine learning and encrypting the secret value using the Advanced Encryption Standard (AES), this system provides robust security. This paper explores the integration of multimodal biometric systems with cryptographic methods to address existing vulnerabilities and improve overall data protection.

Keywords—Biometrics, Multimodal Security, AES Encryption, Machine Learning, Feature Extraction, Bio-Crypto System.